Memory bandwidth reallocation for isochronous traffic

ABSTRACT

The MMU services data requests associated with isochronous (ISO) data (referred to herein as “ISO requests”) with a high priority to meet a fixed latency requirement. Such data includes display data for transmission to the display device or other display devices. Conversely data requests associated with non-isochronous (NISO) data are serviced with a relatively lower priority. Such data requests include requests received from the CPU, video requests and copy requests. The MMU utilizes a buffering mechanism to buffer ISO and NISO requests. The size of the buffer that stores ISO requests controls the amount of memory bandwidth that is allocated to the ISO requests and the amount of memory bandwidth available for NISO requests.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to memory traffic managementand, more specifically, to memory bandwidth reallocation for isochronoustraffic.

2. Description of the Related Art

In a computing system, many different clients compete for access to thememory subsystem. Therefore, certain types of data access requests areprocessed with a high priority to account for the competing access.Further, in some cases, servicing data access requests as quickly aspossible allows for the computing system to save power by turning offthe memory subsystem. Therefore, the data access requests processed witha high priority are also given high memory bandwidth usage to accountfor the “race to sleep” performance conditions. Such race to sleepconditions exist even if no lower priority data access requests exists.

Typically, isochronous data requests, such as display requests in agraphics subsystem, are served by the memory subsystem with a higherpriority than non-isochronous data requests, such as video datarequests. Consequently, in systems having a large amount of isochronousdata request traffic, the memory bandwidth allocated to thenon-isochronous data requests is minimal and non-isochronous datarequests are processed with high latency. Further, during race to sleepcondition, the isochronous data requests can saturate all availablebandwidth for a long time. With no available bandwidth fornon-isochronous requests, such requests suffer very high latency.

Accordingly, what is needed in the art is a system and method forallocating memory bandwidth to different types of data requests in afair manner while also servicing processing priorities and performanceconditions.

SUMMARY OF THE INVENTION

A method for dynamically resizing a buffer configured to storeisochronous data requests. The method includes the steps of determining,based on any outstanding non-isochronous data requests, that the bufferconfigured to store isochronous data requests should be resized, whereinthe size of the buffer indicates an amount of memory bandwidth allocatedto isochronous data requests, determine a new size of the buffer, andresizing the buffer according to the new size.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above recited features of the presentinvention can be understood in detail, a more particular description ofthe invention, briefly summarized above, may be had by reference toembodiments, some of which are illustrated in the appended drawings. Itis to be noted, however, that the appended drawings illustrate onlytypical embodiments of this invention and are therefore not to beconsidered limiting of its scope, for the invention may admit to otherequally effective embodiments.

FIG. 1 is a block diagram illustrating a computer system configured toimplement one or more aspects of the present invention;

FIG. 2 is a block diagram of a parallel processing subsystem for thecomputer system of FIG. 1, according to one embodiment of the presentinvention;

FIG. 3A is a block diagram of the front end of FIG. 2, according to oneembodiment of the present invention;

FIG. 3B is a block diagram of a general processing cluster within one ofthe parallel processing units of FIG. 2, according to one embodiment ofthe present invention;

FIG. 3C is a block diagram of a portion of the streaming multiprocessorof FIG. 3B, according to one embodiment of the present invention;

FIG. 4 is a more detailed illustration of the memory management unit ofFIG. 3B, according to one embodiment of the present invention; and

FIG. 5 is a flow diagram of method steps for dynamically resizing theISO read return buffer according to the current NISO traffic, accordingto one embodiment of the present invention.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth toprovide a more thorough understanding of the present invention. However,it will be apparent to one of skill in the art that the presentinvention may be practiced without one or more of these specificdetails. In other instances, well-known features have not been describedin order to avoid obscuring the present invention.

System Overview

FIG. 1 is a block diagram illustrating a computer system 100 configuredto implement one or more aspects of the present invention. Computersystem 100 includes a central processing unit (CPU) 102 and a systemmemory 104 communicating via an interconnection path that may include amemory bridge 105. Memory bridge 105, which may be, e.g., a Northbridgechip, is connected via a bus or other communication path 106 (e.g., aHyperTransport link) to an I/O (input/output) bridge 107. I/O bridge107, which may be, e.g., a Southbridge chip, receives user input fromone or more user input devices 108 (e.g., keyboard, mouse) and forwardsthe input to CPU 102 via path 106 and memory bridge 105. A parallelprocessing subsystem 112 is coupled to memory bridge 105 via a bus orother communication path 113 (e.g., a Peripheral Component Interconnect(PCI) Express, Accelerated Graphics Port, or HyperTransport link); inone embodiment parallel processing subsystem 112 is a graphics subsystemthat delivers pixels to a display device 110 (e.g., a conventionalcathode ray tube or liquid crystal display based monitor). A system disk114 is also connected to I/O bridge 107. A switch 116 providesconnections between I/O bridge 107 and other components such as anetwork adapter 118 and various add-in cards 120 and 121. Othercomponents (not explicitly shown), including universal serial bus (USB)or other port connections, compact disc (CD) drives, digital video disc(DVD) drives, film recording devices, and the like, may also beconnected to I/O bridge 107. Communication paths interconnecting thevarious components in FIG. 1 may be implemented using any suitableprotocols, such as PCI Express, AGP (Accelerated Graphics Port),HyperTransport, or any other bus or point-to-point communicationprotocol(s), and connections between different devices may use differentprotocols as is known in the art.

In one embodiment, the parallel processing subsystem 112 incorporatescircuitry optimized for graphics and video processing, including, forexample, video output circuitry, and constitutes a graphics processingunit (GPU). In another embodiment, the parallel processing subsystem 112incorporates circuitry optimized for general purpose processing, whilepreserving the underlying computational architecture, described ingreater detail herein. In yet another embodiment, the parallelprocessing subsystem 112 may be integrated with one or more other systemelements, such as the memory bridge 105, CPU 102, and I/O bridge 107 toform a system on chip (SoC).

It will be appreciated that the system shown herein is illustrative andthat variations and modifications are possible. The connection topology,including the number and arrangement of bridges, the number of CPUs 102,and the number of parallel processing subsystems 112, may be modified asdesired. For instance, in some embodiments, system memory 104 isconnected to CPU 102 directly rather than through a bridge, and otherdevices communicate with system memory 104 via memory bridge 105 and CPU102. In other alternative topologies, parallel processing subsystem 112is connected to I/O bridge 107 or directly to CPU 102, rather than tomemory bridge 105. In still other embodiments, I/O bridge 107 and memorybridge 105 might be integrated into a single chip. Large embodiments mayinclude two or more CPUs 102 and two or more parallel processing systems112. The particular components shown herein are optional; for instance,any number of add-in cards or peripheral devices might be supported. Insome embodiments, switch 116 is eliminated, and network adapter 118 andadd-in cards 120, 121 connect directly to I/O bridge 107.

FIG. 2 illustrates a parallel processing subsystem 112, according to oneembodiment of the present invention. As shown, parallel processingsubsystem 112 includes one or more parallel processing units (PPUs) 202,each of which is coupled to a local parallel processing (PP) memory 204.In general, a parallel processing subsystem includes a number U of PPUs,where U≧1. (Herein, multiple instances of like objects are denoted withreference numbers identifying the object and parenthetical numbersidentifying the instance where needed.) PPUs 202 and parallel processingmemories 204 may be implemented using one or more integrated circuitdevices, such as programmable processors, application specificintegrated circuits (ASICs), or memory devices, or in any othertechnically feasible fashion.

Referring again to FIG. 1 as well as FIG. 2, in some embodiments, someor all of PPUs 202 in parallel processing subsystem 112 are graphicsprocessors with rendering pipelines that can be configured to performvarious operations related to generating pixel data from graphics datasupplied by CPU 102 and/or system memory 104 via memory bridge 105 andbus 113, interacting with local parallel processing memory 204 (whichcan be used as graphics memory including, e.g., a conventional framebuffer) to store and update pixel data, delivering pixel data to displaydevice 110, and the like. In some embodiments, parallel processingsubsystem 112 may include one or more PPUs 202 that operate as graphicsprocessors and one or more other PPUs 202 that are used forgeneral-purpose computations. The PPUs may be identical or different,and each PPU may have its own dedicated parallel processing memorydevice(s) or no dedicated parallel processing memory device(s). One ormore PPUs 202 may output data to display device 110 or each PPU 202 mayoutput data to one or more display devices 110.

In operation, CPU 102 is the master processor of computer system 100,controlling and coordinating operations of other system components. Inparticular, CPU 102 issues commands that control the operation of PPUs202. In some embodiments, CPU 102 writes a stream of commands for eachPPU 202 to a data structure (not explicitly shown in either FIG. 1 orFIG. 2) that may be located in system memory 104, parallel processingmemory 204, or another storage location accessible to both CPU 102 andPPU 202. A pointer to each data structure is written to a pushbuffer toinitiate processing of the stream of commands in the data structure. ThePPU 202 reads command streams from one or more pushbuffers and thenexecutes commands asynchronously relative to the operation of CPU 102.Execution priorities may be specified for each pushbuffer to controlscheduling of the different pushbuffers.

Referring back now to FIG. 2 as well as FIG. 1, each PPU 202 includes anI/O (input/output) unit 205 that communicates with the rest of computersystem 100 via communication path 113, which connects to memory bridge105 (or, in one alternative embodiment, directly to CPU 102). Theconnection of PPU 202 to the rest of computer system 100 may also bevaried. In some embodiments, parallel processing subsystem 112 isimplemented as an add-in card that can be inserted into an expansionslot of computer system 100. In other embodiments, a PPU 202 can beintegrated on a single chip with a bus bridge, such as memory bridge 105or I/O bridge 107. In still other embodiments, some or all elements ofPPU 202 may be integrated on a single chip with CPU 102.

In one embodiment, communication path 113 is a PCI Express link, inwhich dedicated lanes are allocated to each PPU 202, as is known in theart. Other communication paths may also be used. An I/O unit 205generates packets (or other signals) for transmission on communicationpath 113 and also receives all incoming packets (or other signals) fromcommunication path 113, directing the incoming packets to appropriatecomponents of PPU 202. For example, commands related to processing tasksmay be directed to a host interface 206, while commands related tomemory operations (e.g., reading from or writing to parallel processingmemory 204) may be directed to a memory crossbar unit 210. Hostinterface 206 reads each pushbuffer and outputs the command streamstored in the pushbuffer to a front end 212.

Each PPU 202 advantageously implements a highly parallel processingarchitecture. As shown in detail, PPU 202(0) includes a processingcluster array 230 that includes a number C of general processingclusters (GPCs) 208, where C≧1. Each GPC 208 is capable of executing alarge number (e.g., hundreds or thousands) of threads concurrently,where each thread is an instance of a program. In various applications,different GPCs 208 may be allocated for processing different types ofprograms or for performing different types of computations. Theallocation of GPCs 208 may vary dependent on the workload arising foreach type of program or computation.

GPCs 208 receive processing tasks to be executed from a workdistribution unit within a task/work unit 207. The work distributionunit receives pointers to processing tasks that are encoded as taskmetadata (TMD) and stored in memory. The pointers to TMDs are includedin the command stream that is stored as a pushbuffer and received by thefront end unit 212 from the host interface 206. Processing tasks thatmay be encoded as TMDs include indices of data to be processed, as wellas state parameters and commands defining how the data is to beprocessed (e.g., what program is to be executed). The task/work unit 207receives tasks from the front end 212 and ensures that GPCs 208 areconfigured to a valid state before the processing specified by each oneof the TMDs is initiated. A priority may be specified for each TMD thatis used to schedule execution of the processing task.

Memory interface 214 includes a number D of partition units 215 that areeach directly coupled to a portion of parallel processing memory 204,where D≧1. As shown, the number of partition units 215 generally equalsthe number of dynamic random access memory (DRAM) 220. In otherembodiments, the number of partition units 215 may not equal the numberof memory devices. Persons of ordinary skill in the art will appreciatethat DRAM 220 may be replaced with other suitable storage devices andcan be of generally conventional design. A detailed description istherefore omitted. Render targets, such as frame buffers or texture mapsmay be stored across DRAMs 220, allowing partition units 215 to writeportions of each render target in parallel to efficiently use theavailable bandwidth of parallel processing memory 204.

Any one of GPCs 208 may process data to be written to any of the DRAMs220 within parallel processing memory 204. Crossbar unit 210 isconfigured to route the output of each GPC 208 to the input of anypartition unit 215 or to another GPC 208 for further processing. GPCs208 communicate with memory interface 214 through crossbar unit 210 toread from or write to various external memory devices. In oneembodiment, crossbar unit 210 has a connection to memory interface 214to communicate with I/O unit 205, as well as a connection to localparallel processing memory 204, thereby enabling the processing coreswithin the different GPCs 208 to communicate with system memory 104 orother memory that is not local to PPU 202. In the embodiment shown inFIG. 2, crossbar unit 210 is directly connected with I/O unit 205.Crossbar unit 210 may use virtual channels to separate traffic streamsbetween the GPCs 208 and partition units 215.

Again, GPCs 208 can be programmed to execute processing tasks relatingto a wide variety of applications, including but not limited to, linearand nonlinear data transforms, filtering of video and/or audio data,modeling operations (e.g., applying laws of physics to determineposition, velocity and other attributes of objects), image renderingoperations (e.g., tessellation shader, vertex shader, geometry shader,and/or pixel shader programs), and so on. PPUs 202 may transfer datafrom system memory 104 and/or local parallel processing memories 204into internal (on-chip) memory, process the data, and write result databack to system memory 104 and/or local parallel processing memories 204,where such data can be accessed by other system components, includingCPU 102 or another parallel processing subsystem 112.

A PPU 202 may be provided with any amount of local parallel processingmemory 204, including no local memory, and may use local memory andsystem memory in any combination. For instance, a PPU 202 can be agraphics processor in a unified memory architecture (UMA) embodiment. Insuch embodiments, little or no dedicated graphics (parallel processing)memory would be provided, and PPU 202 would use system memoryexclusively or almost exclusively. In UMA embodiments, a PPU 202 may beintegrated into a bridge chip or processor chip or provided as adiscrete chip with a high-speed link (e.g., PCI Express) connecting thePPU 202 to system memory via a bridge chip or other communication means.

As noted above, any number of PPUs 202 can be included in a parallelprocessing subsystem 112. For instance, multiple PPUs 202 can beprovided on a single add-in card, or multiple add-in cards can beconnected to communication path 113, or one or more of PPUs 202 can beintegrated into a bridge chip. PPUs 202 in a multi-PPU system may beidentical to or different from one another. For instance, different PPUs202 might have different numbers of processing cores, different amountsof local parallel processing memory, and so on. Where multiple PPUs 202are present, those PPUs may be operated in parallel to process data at ahigher throughput than is possible with a single PPU 202. Systemsincorporating one or more PPUs 202 may be implemented in a variety ofconfigurations and form factors, including desktop, laptop, or handheldpersonal computers, servers, workstations, game consoles, embeddedsystems, and the like.

Multiple Concurrent Task Scheduling

Multiple processing tasks may be executed concurrently on the GPCs 208and a processing task may generate one or more “child” processing tasksduring execution. The task/work unit 207 receives the tasks anddynamically schedules the processing tasks and child processing tasksfor execution by the GPCs 208.

FIG. 3A is a block diagram of the task/work unit 207 of FIG. 2,according to one embodiment of the present invention. The task/work unit207 includes a task management unit 300 and the work distribution unit340. The task management unit 300 organizes tasks to be scheduled basedon execution priority levels. For each priority level, the taskmanagement unit 300 stores a list of pointers to the TMDs 322corresponding to the tasks in the scheduler table 321, where the listmay be implemented as a linked list. The TMDs 322 may be stored in thePP memory 204 or system memory 104. The rate at which the taskmanagement unit 300 accepts tasks and stores the tasks in the schedulertable 321 is decoupled from the rate at which the task management unit300 schedules tasks for execution, enabling the task management unit 300to schedule tasks based on priority information or using othertechniques.

The work distribution unit 340 includes a task table 345 with slots thatmay each be occupied by the TMD 322 for a task that is being executed.The task management unit 300 may schedule tasks for execution when thereis a free slot in the task table 345. When there is not a free slot, ahigher priority task that does not occupy a slot may evict a lowerpriority task that does occupy a slot. When a task is evicted, the taskis stopped, and if execution of the task is not complete, then the taskis added to a linked list in the scheduler table 321. When a childprocessing task is generated, the child task is added to a linked listin the scheduler table 321. A child task may be generated by a TMD 322executing in the processing cluster array 230. A task is removed from aslot when the task is evicted.

Task Processing Overview

FIG. 3B is a block diagram of a GPC 208 within one of the PPUs 202 ofFIG. 2, according to one embodiment of the present invention. Each GPC208 may be configured to execute a large number of threads in parallel,where the term “thread” refers to an instance of a particular programexecuting on a particular set of input data. In some embodiments,single-instruction, multiple-data (SIMD) instruction issue techniquesare used to support parallel execution of a large number of threadswithout providing multiple independent instruction units. In otherembodiments, single-instruction, multiple-thread (SIMT) techniques areused to support parallel execution of a large number of generallysynchronized threads, using a common instruction unit configured toissue instructions to a set of processing engines within each one of theGPCs 208. Unlike a SIMD execution regime, where all processing enginestypically execute identical instructions, SIMT execution allowsdifferent threads to more readily follow divergent execution pathsthrough a given thread program. Persons of ordinary skill in the artwill understand that a SIMD processing regime represents a functionalsubset of a SIMT processing regime.

Operation of GPC 208 is advantageously controlled via a pipeline manager305 that distributes processing tasks to streaming multiprocessors (SMs)310. Pipeline manager 305 may also be configured to control a workdistribution crossbar 330 by specifying destinations for processed dataoutput by SMs 310.

In one embodiment, each GPC 208 includes a number M of SMs 310, whereM≧1, each SM 310 is configured to process one or more thread groups.Also, each SM 310 advantageously includes an identical set of functionalexecution units (e.g., execution units and load-store units—shown asExec units 302 and LSUs 303 in FIG. 3C) that may be pipelined, allowinga new instruction to be issued before a previous instruction hasfinished, as is known in the art. Any combination of functionalexecution units may be provided. In one embodiment, the functional unitssupport a variety of operations including integer and floating pointarithmetic (e.g., addition and multiplication), comparison operations,Boolean operations (AND, OR, XOR), bit-shifting, and computation ofvarious algebraic functions (e.g., planar interpolation, trigonometric,exponential, and logarithmic functions, etc.); and the same functionalunit hardware can be leveraged to perform different operations.

The series of instructions transmitted to a particular GPC 208constitutes a thread, as previously defined herein, and the collectionof a certain number of concurrently executing threads across theparallel processing engines (not shown) within an SM 310 is referred toherein as a “warp” or “thread group.” As used herein, a “thread group”refers to a group of threads concurrently executing the same program ondifferent input data, with one thread of the group being assigned to adifferent processing engine within an SM 310. A thread group may includefewer threads than the number of processing engines within the SM 310,in which case some processing engines will be idle during cycles whenthat thread group is being processed. A thread group may also includemore threads than the number of processing engines within the SM 310, inwhich case processing will take place over consecutive clock cycles.Since each SM 310 can support up to G thread groups concurrently, itfollows that up to G*M thread groups can be executing in GPC 208 at anygiven time.

Additionally, a plurality of related thread groups may be active (indifferent phases of execution) at the same time within an SM 310. Thiscollection of thread groups is referred to herein as a “cooperativethread array” (“CTA”) or “thread array.” The size of a particular CTA isequal to m*k, where k is the number of concurrently executing threads ina thread group and is typically an integer multiple of the number ofparallel processing engines within the SM 310, and m is the number ofthread groups simultaneously active within the SM 310. The size of a CTAis generally determined by the programmer and the amount of hardwareresources, such as memory or registers, available to the CTA.

Each SM 310 contains a level one (L1) cache (shown in FIG. 3C) or usesspace in a corresponding L1 cache outside of the SM 310 that is used toperform load and store operations. Each SM 310 also has access to leveltwo (L2) caches that are shared among all GPCs 208 and may be used totransfer data between threads. Finally, SMs 310 also have access tooff-chip “global” memory, which can include, e.g., parallel processingmemory 204 and/or system memory 104. It is to be understood that anymemory external to PPU 202 may be used as global memory. Additionally, alevel one-point-five (L1.5) cache 335 may be included within the GPC208, configured to receive and hold data fetched from memory via memoryinterface 214 requested by SM 310, including instructions, uniform data,and constant data, and provide the requested data to SM 310. Embodimentshaving multiple SMs 310 in GPC 208 beneficially share commoninstructions and data cached in L1.5 cache 335.

Each GPC 208 may include a memory management unit (MMU) 328 that isconfigured to map virtual addresses into physical addresses. In otherembodiments, MMU(s) 328 may reside within the memory interface 214. TheMMU 328 includes a set of page table entries (PTEs) used to map avirtual address to a physical address of a tile and optionally a cacheline index. The MMU 328 may include address translation lookasidebuffers (TLB) or caches which may reside within multiprocessor SM 310 orthe L1 cache or GPC 208. The physical address is processed to distributesurface data access locality to allow efficient request interleavingamong partition units. The cache line index may be used to determinewhether or not a request for a cache line is a hit or miss.

In graphics and computing applications, a GPC 208 may be configured suchthat each SM 310 is coupled to a texture unit 315 for performing texturemapping operations, e.g., determining texture sample positions, readingtexture data, and filtering the texture data. Texture data is read froman internal texture L1 cache (not shown) or in some embodiments from theL1 cache within SM 310 and is fetched from an L2 cache, parallelprocessing memory 204, or system memory 104, as needed. Each SM 310outputs processed tasks to work distribution crossbar 330 in order toprovide the processed task to another GPC 208 for further processing orto store the processed task in an L2 cache, parallel processing memory204, or system memory 104 via crossbar unit 210. A preROP (pre-rasteroperations) 325 is configured to receive data from SM 310, direct datato ROP units within partition units 215, and perform optimizations forcolor blending, organize pixel color data, and perform addresstranslations.

It will be appreciated that the core architecture described herein isillustrative and that variations and modifications are possible. Anynumber of processing units, e.g., SMs 310 or texture units 315, preROPs325 may be included within a GPC 208. Further, while only one GPC 208 isshown, a PPU 202 may include any number of GPCs 208 that areadvantageously functionally similar to one another so that executionbehavior does not depend on which GPC 208 receives a particularprocessing task. Further, each GPC 208 advantageously operatesindependently of other GPCs 208 using separate and distinct processingunits, L1 caches, and so on.

Persons of ordinary skill in the art will understand that thearchitecture described in FIGS. 1, 2, 3A, and 3B in no way limits thescope of the present invention and that the techniques taught herein maybe implemented on any properly configured processing unit, including,without limitation, one or more CPUs, one or more multi-core CPUs, oneor more PPUs 202, one or more GPCs 208, one or more graphics or specialpurpose processing units, or the like, without departing the scope ofthe present invention.

In embodiments of the present invention, it is desirable to use PPU 202or other processor(s) of a computing system to execute general-purposecomputations using thread arrays. Each thread in the thread array isassigned a unique thread identifier (“thread ID”) that is accessible tothe thread during the thread's execution. The thread ID, which can bedefined as a one-dimensional or multi-dimensional numerical valuecontrols various aspects of the thread's processing behavior. Forinstance, a thread ID may be used to determine which portion of theinput data set a thread is to process and/or to determine which portionof an output data set a thread is to produce or write.

A sequence of per-thread instructions may include at least oneinstruction that defines a cooperative behavior between therepresentative thread and one or more other threads of the thread array.For example, the sequence of per-thread instructions might include aninstruction to suspend execution of operations for the representativethread at a particular point in the sequence until such time as one ormore of the other threads reach that particular point, an instructionfor the representative thread to store data in a shared memory to whichone or more of the other threads have access, an instruction for therepresentative thread to atomically read and update data stored in ashared memory to which one or more of the other threads have accessbased on their thread IDs, or the like. The CTA program can also includean instruction to compute an address in the shared memory from whichdata is to be read, with the address being a function of thread ID. Bydefining suitable functions and providing synchronization techniques,data can be written to a given location in shared memory by one threadof a CTA and read from that location by a different thread of the sameCTA in a predictable manner. Consequently, any desired pattern of datasharing among threads can be supported, and any thread in a CTA canshare data with any other thread in the same CTA. The extent, if any, ofdata sharing among threads of a CTA is determined by the CTA program;thus, it is to be understood that in a particular application that usesCTAs, the threads of a CTA might or might not actually share data witheach other, depending on the CTA program, and the terms “CTA” and“thread array” are used synonymously herein.

FIG. 3C is a block diagram of the SM 310 of FIG. 3B, according to oneembodiment of the present invention. The SM 310 includes an instructionL1 cache 370 that is configured to receive instructions and constantsfrom memory via L1.5 cache 335. A warp scheduler and instruction unit312 receives instructions and constants from the instruction L1 cache370 and controls local register file 304 and SM 310 functional unitsaccording to the instructions and constants. The SM 310 functional unitsinclude N exec (execution or processing) units 302 and P load-storeunits (LSU) 303.

SM 310 provides on-chip (internal) data storage with different levels ofaccessibility. Special registers (not shown) are readable but notwriteable by LSU 303 and are used to store parameters defining eachthread's “position.” In one embodiment, special registers include oneregister per thread (or per exec unit 302 within SM 310) that stores athread ID; each thread ID register is accessible only by a respectiveone of the exec unit 302. Special registers may also include additionalregisters, readable by all threads in the same grid or queue (or by allLSUs 303) that store a CTA identifier, the CTA dimensions, thedimensions of a grid to which the CTA belongs (or queue position if aqueue), and an identifier of the grid or queue to which the CTA belongs.CTAs that belong to a grid have implicit x,y,z parameters indicating theposition of the respective CTA within the grid. Special registers arewritten during initialization in response to commands received via frontend 212 from device driver 103 and do not change during execution of aprocessing task. The front end 212 schedules each processing task forexecution as either a grid or queue. Each CTA is associated with aspecific grid or queue for concurrent execution of one or more tasks.Additionally, a single GPC 208 may execute multiple tasks concurrently.

A parameter memory (not shown) stores runtime parameters (constants)that can be read but not written by any thread within the same CTA (orany LSU 303). In one embodiment, device driver 103 provides parametersto the parameter memory before directing SM 310 to begin execution of atask that uses these parameters. Any thread within any CTA (or any execunit 302 within SM 310) can access global memory through a memoryinterface 214. Portions of global memory may be stored in the L1 cache320.

Local register file 304 is used by each thread as scratch space; eachregister is allocated for the exclusive use of one thread, and data inany of local register file 304 is accessible only to the thread to whichthe register is allocated. Local register file 304 can be implemented asa register file that is physically or logically divided into P lanes,each having some number of entries (where each entry might store, e.g.,a 32-bit word). One lane is assigned to each of the N exec units 302 andP load-store units LSU 303, and corresponding entries in different lanescan be populated with data for different threads executing the sameprogram to facilitate SIMD execution. Different portions of the lanescan be allocated to different ones of the G concurrent thread groups, sothat a given entry in the local register file 304 is accessible only toa particular thread. In one embodiment, certain entries within the localregister file 304 are reserved for storing thread identifiers,implementing one of the special registers. Additionally, a uniform L1cache 375 stores uniform or constant values for each lane of the N execunits 302 and P load-store units LSU 303.

Shared memory 306 is accessible to threads within a single CTA; in otherwords, any location in shared memory 306 is accessible to any threadwithin the same CTA (or to any processing engine within SM 310). Sharedmemory 306 can be implemented as a shared register file or sharedon-chip cache memory with an interconnect that allows any processingengine to read from or write to any location in the shared memory. Inother embodiments, shared state space might map onto a per-CTA region ofoff-chip memory, and be cached in L1 cache 320. The parameter memory canbe implemented as a designated section within the same shared registerfile or shared cache memory that implements shared memory 306, or as aseparate shared register file or on-chip cache memory to which the LSUs303 have read-only access. In one embodiment, the area that implementsthe parameter memory is also used to store the CTA ID and task ID, aswell as CTA and grid dimensions or queue position, implementing portionsof the special registers. Each LSU 303 in SM 310 is coupled to a unifiedaddress mapping unit 352 that converts an address provided for load andstore instructions that are specified in a unified memory space into anaddress in each distinct memory space. Consequently, an instruction maybe used to access any of the local, shared, or global memory spaces byspecifying an address in the unified memory space.

The L1 cache 320 in each SM 310 can be used to cache private per-threadlocal data and also per-application global data. In some embodiments,the per-CTA shared data may be cached in the L1 cache 320. The LSUs 303are coupled to the shared memory 306 and the L1 cache 320 via a memoryand cache interconnect 380.

Dynamic Resizing of Isochronous Read Return Buffer

The MMU 328 routes data requests associated with isochronous andnon-isochronous data to the memory interface 214 via the crossbar unit210 (FIG. 2). The MMU 328, the crossbar unit 210 and the partition unit215 service data requests associated with isochronous (ISO) data(referred to herein as “ISO requests”) with a high priority to meet afixed latency requirement. Such data includes display data fortransmission to the display device 110 (FIG. 1) or other displaydevices. Conversely data requests associated with non-isochronous (NISO)data (referred to herein as “NISO requests”) are serviced with arelatively lower priority. Such data requests include requests receivedfrom the CPU 102, video requests and copy requests. The MMU 328 utilizesa buffering mechanism to buffer ISO and NISO requests. The size of thebuffer that stores ISO requests controls the amount of memory bandwidththat is allocated to the ISO requests and the amount of memory bandwidthavailable for NISO requests.

FIG. 4 is a more detailed illustration of the memory management unit(MMU) 328 of FIG. 3B, according to one embodiment of the presentinvention. As shown, the MMU 328 includes an arbiter 402, anon-isochronous (NISO) read return buffer 404, an isochronous (ISO) readreturn buffer 406, resizing logic 408 and a memory controller 410.

Data requests received from the CPU 102, video data requests and copydata requests are typically considered non-isochronous data requests.These requests are input into the arbiter 402, which selects the orderin which the non-isochronous data requests are input into the NISO readreturn buffer 404. The size of the NISO read return buffer 404 islimited, such that, at any given time, only a pre-determined number ofnon-isochronous data requests can be serviced by the NISO read returnbuffer 404. The non-isochronous data requests are stalled until the NISOread return buffer 404 can service those non-isochronous data requests.

Display data requests are typically considered as isochronous datarequests. These requests, when received, are stalled until the ISO readreturn buffer 406 can service those requests. When the ISO read returnbuffer 406 can service a request, the request is transmitted to thememory interface 214 via the memory controller 410. The size of the ISOread return buffer 406 controls the amount of memory bandwidth that isallocated to the ISO requests and the amount of memory bandwidthavailable for NISO requests. In operation, the amount of memorybandwidth needed to service the ISO requests according to pre-determinedlatency requirements is allocated to the ISO requests and any residualbandwidth is allocated to the NISO requests.

In operation, the resizing logic 408 monitors the currentnon-isochronous data request traffic and accordingly modifies the sizeof the ISO read return buffer 406 such that memory bandwidth availableto both ISO requests and NISO requests matches the overall systemrequirements. The resizing logic 408 determines the size of the ISO readreturn buffer at any given time based on one or more heuristics relatedto the current non-isochronous data request traffic. One heuristic maybe the existence of NISO requests, such that, when NISO requests exist,the size of the ISO read return buffer 406 is reduced. Reducing the sizeof the ISO read return buffer 406 reduces the amount of memory bandwidththat is allocated to ISO requests and increases the amount of memorybandwidth available for NISO requests. Another heuristic may be theexistence of a particular type of data requests in the NISO read returnbuffer 404. For example, if the NISO read return buffer 404 stores CPUdata requests, then the resizing logic 408 may reduce the size of theISO read return buffer by a greater amount relative to the existence ofother types of NISO requests. Further, when no NISO requests exist, theresizing logic 408 may increase the size of the ISO read return buffer406 such that a maximum amount of memory bandwidth is available for ISOrequests. Persons skilled in the art would recognize that any otherheuristic related to the current non-isochronous data request trafficbased on which the resizing logic 408 computes the size of the ISO readreturn buffer 406 is within the scope of the invention.

In one embodiment, the resizing functionality implemented by theresizing logic 408 is enabled or disabled based on the currentrequirements of the overall system.

Further, in one embodiment, the device driver 103 configures theresizing logic 408 to resize the ISO read return buffer 406 topre-determined sizes based on the amount and type of NISO requests. Forexample, the device driver 103 may configure the resizing logic 408 suchthat when NISO requests exist, the resizing logic 408 reduces the sizeof the ISO read return buffer 406 to support a fifty percent availablememory bandwidth allocation to the NISO requests. In such a case, thesize of the buffer is calculated as fifty percent of the total memorybandwidth multiplied by the worst case latency for ISO divided by thesize of every entry in the ISO read return buffer 406. Any othermechanism used by the driver to calculate the size of the ISO readreturn buffer 406 is within the scope of this invention.

In an alternate embodiment, the resizing logic 408 computes the amountthat the size of the ISO read return buffer 406 is increased ordecreased based on the current non-isochronous data request trafficwithout the involvement of the device driver 103. For example, theresizing logic 408 may calculate a value indicating the ratio of thememory bandwidth clock to the clock running the ISO read return buffer406 and then tune the value according to the rate of data return. Again,any other mechanism used by the resizing logic to calculate the size ofthe ISO read return buffer 406 is within the scope of this invention.

ISO requests serviced by the ISO read return buffer 406 and NISOrequests serviced by the NISO read return buffer 404 are transmitted tothe memory controller 410, which transmits those requests to the memoryinterface 214 for processing. Again, the amount of memory bandwidthavailable to each of the ISO requests and the NISO requests isdetermined based on the size of the ISO read return buffer 406, i.e.,the bigger the size, the more memory bandwidth is used by ISO requests.

FIG. 5 is a flow diagram of method steps for dynamically resizing theISO read return buffer according to the current NISO traffic, accordingto one embodiment of the present invention. Although the method stepsare described in conjunction with FIGS. 1-4, persons skilled in the artwill understand that any system configured to perform the method steps,in any order, falls within the scope of the present invention.

The method 500 begins at step 502, where the resizing logic 408determines whether the resizing of the ISO read return buffer 406 isenabled or disabled. At step 504, if the resizing of the ISO read returnbuffer 406 is disabled, then the method 500 ends. However, if theresizing of the ISO read return buffer 406 is enabled, then the method500 proceeds to step 506.

At step 506, the resizing logic 408 monitors the current non-isochronousdata request traffic and determines whether the ISO read return buffer406 should be resized. In one embodiment, the existence of NISO requestsor the existence of a particular type of NISO request is used todetermined whether the ISO read return buffer 406 should be resized. Atstep 504, if the ISO read return buffer 406 should not be resized, thenthe method 500 returns back to step 506, where the resizing logic 408continues to monitor the current NISO request traffic. However, if theISO read return buffer 406 should be resized, then the method 500proceeds to step 510.

At step 510, the resizing logic 408 determines the size of the ISO readreturn buffer 406 based on one or more heuristics related to the currentnon-isochronous data request traffic. For example, the heuristics mayinclude the amount of isochronous data request traffic or the existenceof a particular type of isochronous data request traffic. Again, theamount of memory bandwidth available to each of the ISO requests and theNISO requests is determined based on the size of the ISO read returnbuffer 406, i.e., the bigger the size, the more memory bandwidth is usedby ISO requests. At step 512, the resizing logic 408 resizes the ISOread return buffer 406 to the determined size. By resizing the ISO readreturn buffer 406 to a particular size, the amount of memory bandwidthavailable to each of the ISO requests and the NISO requests iscontrolled

Advantageously, dynamically resizing the ISO read return buffer based onthe current NISO request traffic allocates memory bandwidth to ISOrequests and NISO requests in a fair manner. In cases where NISOrequests do not exist, the ISO requests are allocated maximum memorybandwidth and, therefore, are processed faster and the system canachieve “race to sleep” performance conditions. In cases where NISOrequests do exist, some amount of memory bandwidth is allocated to theNISO requests to ensure that those requests are processed along with ISOrequests and that the ISO requests are not consuming all availablebandwidth.

One embodiment of the invention may be implemented as a program productfor use with a computer system. The program(s) of the program productdefine functions of the embodiments (including the methods describedherein) and can be contained on a variety of computer-readable storagemedia. Illustrative computer-readable storage media include, but are notlimited to: (i) non-writable storage media (e.g., read-only memorydevices within a computer such as compact disc read only memory (CD-ROM)disks readable by a CD-ROM drive, flash memory, read only memory (ROM)chips or any type of solid-state non-volatile semiconductor memory) onwhich information is permanently stored; and (ii) writable storage media(e.g., floppy disks within a diskette drive or hard-disk drive or anytype of solid-state random-access semiconductor memory) on whichalterable information is stored.

The invention has been described above with reference to specificembodiments. Persons of ordinary skill in the art, however, willunderstand that various modifications and changes may be made theretowithout departing from the broader spirit and scope of the invention asset forth in the appended claims. The foregoing description and drawingsare, accordingly, to be regarded in an illustrative rather than arestrictive sense.

The invention claimed is:
 1. A computer implemented method fordynamically resizing a buffer configured to store data associated withisochronous data requests, the method comprising: determining, based onan amount of outstanding non-isochronous data requests, that the bufferconfigured to store data associated with isochronous data requestsshould be resized; determining a new size of the buffer based on theamount of outstanding non-isochronous data requests and a ratio of amemory clock to a clock running the buffer; and resizing the bufferaccording to the new size.
 2. The method of claim 1, wherein the newsize of the buffer is smaller than the current size of the buffer. 3.The method of claim 2, wherein determining that the buffer configured tostore data associated with isochronous data requests should be resizedcomprises determining that one or more non-isochronous data requestsexist.
 4. The method of claim 2, wherein determining that the bufferconfigured to store data associated with isochronous data requestsshould be resized comprises determining that one or more non-isochronousdata requests of a particular type exist.
 5. The method of claim 1,wherein the new size of the buffer is larger than the current size ofthe buffer.
 6. The method of claim 1, wherein determining that thebuffer configured to store data associated with isochronous datarequests should be resized comprises determining that no non-isochronousdata requests exist.
 7. The method of claim 6, wherein the new size ofthe buffer is a maximum size for the buffer.
 8. The method of claim 1,further comprising determining that buffer resizing functionality isenabled.
 9. The method of claim 1, wherein the new size of the buffer ispre-determined by a device driver.
 10. The method of claim 1, whereinthe size of the buffer configured to store data associated with theisochronous data requests controls a first amount of memory bandwidththat is allocated to the isochronous data requests and a second amountof memory bandwidth that is allocated to the outstanding non-isochronousdata requests.
 11. A non-transitory computer readable medium storinginstructions that, when executed by a processor, cause the processor todynamically resize a buffer configured to store data associated withisochronous data requests, by performing the steps of: determining,based on an amount of outstanding non-isochronous data requests, thatthe buffer configured to store data associated with isochronous datarequests should be resized; determining a new size of the buffer basedon the amount of outstanding non-isochronous data requests and a ratioof a memory clock to a clock running the buffer; and resizing the bufferaccording to the new size.
 12. The computer readable medium of claim 11,wherein the new size of the buffer is smaller than the current size ofthe buffer.
 13. The computer readable medium of claim 12, whereindetermining that the buffer configured to store data associated withisochronous data requests should be resized comprises determining thatone or more non-isochronous data requests exist.
 14. The computerreadable medium of claim 12, wherein determining that the bufferconfigured to store data associated with isochronous data requestsshould be resized comprises determining that one or more non-isochronousdata requests of a particular type exist.
 15. The computer readablemedium of claim 11, wherein the new size of the buffer is larger thanthe current size of the buffer.
 16. The computer readable medium ofclaim 11, wherein determining that the buffer configured to store dataassociated with isochronous data requests should be resized comprisesdetermining that no non-isochronous data requests exist.
 17. Thecomputer readable medium of claim 16, wherein the new size of the bufferis a maximum size for the buffer.
 18. The computer readable medium ofclaim 11, further comprising determining that buffer resizingfunctionality is enabled.
 19. The computer readable medium of claim 11,wherein the new size of the buffer is pre-determined by a device driver.20. A computer system, comprising: a memory management unit thatincludes: a buffer configured to store data associated with isochronousdata requests, and resizing logic configured to: determine, based on anamount of outstanding non-isochronous data requests, that the bufferconfigured to store data associated with isochronous data requestsshould be resized, determine a new size of the buffer based on theamount of outstanding non-isochronous data requests and a ratio of amemory clock to a clock running the buffer, and resize the bufferaccording to the new size.
 21. The computer system of claim 20, furthercomprising a memory interface unit configured to process isochronousdata requests and non-isochronous data requests received from the memorymanagement unit.